maxCorners – Maximum number of corners to return. If there are more corners than are found, the strongest of them is returned.

qualityLevel – Parameter characterizing the minimal accepted quality of image corners. The parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue (see gpu::cornerMinEigenVal() ) or the Harris function response (see gpu::cornerHarris() ). The corners with the quality measure less than the product are rejected. For example, if the best corner has the quality measure = 1500, and the qualityLevel=0.01 , then all the corners with the quality measure less than 15 are rejected.

minDistance – Minimum possible Euclidean distance between the returned corners.

blockSize – Size of an average block for computing a derivative covariation matrix over each pixel neighborhood. See cornerEigenValsAndVecs() .

nextImg – Second input image of the same size and the same type as prevImg .

prevPts – Vector of 2D points for which the flow needs to be found. It must be one row matrix with CV_32FC2 type.

nextPts – Output vector of 2D points (with single-precision floating-point coordinates) containing the calculated new positions of input features in the second image. When useInitialFlow is true, the vector must have the same size as in the input.

status – Output status vector (CV_8UC1 type). Each element of the vector is set to 1 if the flow for the corresponding features has been found. Otherwise, it is set to 0.

err – Output vector (CV_32FC1 type) that contains min eigen value. It can be NULL, if not needed.